1. Field of the Invention
The present invention relates to a method for designing a blade shape in a blade cascade of an axial compressor.
2. Description of the Related Art
The shape of a blade in a blade cascade of an axial compressor affects performances of the axial compressor largely. Various trials or tests for optimizing the shape of a blade have been made. In Japanese Patent Application Laid-Open (KOKAI) No. 10-149384, there has been disclosed a designing method characterized in that, in order that pressure loss may be optimized while objective functions about many design variables are evaluated, a compressive viscous fluid equation is solved and the computation time required for the solution does not depend on the number of design variables.
In detail, by solving simultaneous linear equations of the same order with a compressive viscous fluid equation derived from an implicit function theorem, only once, a gradient of objective functions about many design variables can be obtained simultaneously. As the objective functions or restraints, an outflow angle of fluid downstream the blade cascade, a pressure gradient on a blade surface and the like are adopted.
As understood from the above, it is one of important problems in design of an axial compressor to design a blade shape in consideration of various design variables.
When the conventional method based upon the gradient is employed, a local optimal solution can be obtained in some cases. Also, even when an actual or desirable optimal solution is obtained, it is difficult to determine whether or not the solution is the actual optimal solution. Furthermore, the method has such a disadvantage that it is not coincident with non-linearity and discontinuity of aerodynamic evaluation occurring in a change of profile and therefore it has less flexibility to various applications. For this reason, recently, the traditional gradient based methods have been giving way to statistic methods using evolutionary algorithms (EAs) and artificial neural networks (ANNs) which are easily adjustable to the non-linearity and have a flexibility for various applications.